docs: def read(path, corpus=True, index_by='uri', follow_links=False, **kwargs):
      """
      Read bibliographic data from Zotero RDF.
  
      Examples
      --------
      Assuming that the Zotero collection was exported to the directory
      ``/my/working/dir`` with the name ``myCollection``, a subdirectory should
      have been created at ``/my/working/dir/myCollection``, and an RDF file
      should exist at ``/my/working/dir/myCollection/myCollection.rdf``.
  
      .. code-block:: python
  
         >>> from tethne.readers.zotero import read
         >>> myCorpus = read('/my/working/dir/myCollection')
         >>> myCorpus
         <tethne.classes.corpus.Corpus object at 0x10047e350>
  
  
      Parameters
      ----------
      path : str
          Path to the output directory created by Zotero. Expected to contain a
          file called ``[directory_name].rdf``.
      corpus : bool
          (default: True) If True, returns a :class:`.Corpus`\. Otherwise,
          returns a list of :class:`.Paper`\s.
      index_by : str
          (default: ``'identifier'``) :class:`.Paper` attribute name to use as
          the primary indexing field. If the field is missing on a
          :class:`.Paper`\, a unique identifier will be generated based on the
          title and author names.
      follow_links : bool
          If ``True``, attempts to load full-text content from attached files
          (e.g. PDFs with embedded text). Default: False.
      kwargs : kwargs
          Passed to the :class:`.Corpus` constructor.
  
      Returns
      -------
      corpus : :class:`.Corpus`
      """
      # TODO: is there a case where `from_dir` would make sense?
  
      parser = ZoteroParser(path, index_by=index_by, follow_links=follow_links)
      papers = parser.parse()
  
      if corpus:
          c = Corpus(papers, index_by=index_by, **kwargs)
          if c.duplicate_papers:
              warnings.warn("Duplicate papers detected. Use the 'duplicate_papers' attribute of the corpus to get the list", UserWarning)
  
          for fset_name, fset_values in parser.full_text.iteritems():
              c.features[fset_name] = StructuredFeatureSet(fset_values)
          return c
      return papers